Open Data

IT operations analytics

In the fields of information technology (IT) and systems management , IT operations (ITOA) is an approach or method to retrieve, analyze, and report data for IT operations. ITOA may apply big data analytics to large datasets to produce business insights. [1] [2] In 2014, Gartner predicted its use to increase revenue or reduce costs. [3] By 2017, it is predicted that 15% of enterprises will use IT operations analytics technologies. [2]

Definition

IT operations (ITOA) (also known as advanced operational analytics, [4] or IT data analytics [5] ) are mainly used to discover complex patterns in high volumes of often “noisy” IT system availability and performance data. [6] Forrester Research defined IT analytics as “The use of mathematical algorithms and other innovations to extract meaningful information from the world of raw data collected by management and monitoring technologies.” [7]

History

Operations research as a discipline emerged from the Second World War to improve military efficiency and decision-making on the battlefield. [8] However, only with the emergence of machine learning technology in the early 2000s could an artificially intelligent operational analytics platform actually begin to engage in the high-level pattern of recognition . [1] A critical catalyst towards ITOA development of Google , which pioneered a predictive analytics model that represents the first attempt to read patterns of human behavior on the Internet. IT specialists then applied to the IT industry, coming forward with platforms that can be used to reduce the risk of injury. [1]

Due the mainstream embrace of cloud computing and the Increasing desire for businesses to adopt more Big Data practices, the industry ITOA HAS Significantly grown since 2010. A 2016 survey of ExtraHop wide and mid-size corporations That indicates 65 percent of the businesses surveyed will seek their data silos or this year or the next. [9] The current goals of ITOA are to improve the accuracy of their APM services, and to improve their predictive analytics capabilities.

Applications

ITOA systems tend to be used by IT operations teams, and Gartner describes five applications of ITOA systems: [10]

Root Cause Analysis: The models, structures and pattern descriptions of IT infrastructure or application stack.

Proactive Control of Service Performance and Availability: Predicting future system states and the impact of those states on performance.

Problem Assignment: Determines how problems can be resolved, or at least, the results of the problem.

Impact Analysis Service: When multiple root causes are known, the analytics system is used to determine the relative impact, so that resources can be allocated to correcting the fault in the most timely and cost-effective way possible.

Complement Best-of-breed Technology: The models, structures and pattern descriptions of IT infrastructure or application stack being used to improve the performance of other tools. service dependency maps, application runtime architecture topologies, network topologies).

Real time application behavior learning: Learns & correlates the behavior of Application based on the user and the underlying framework.

Dynamically Baselines Threshold: Learns the behavior of different types of infrastructure and the use of different types of devices. and user patterns

Types

In their Data Growth Demands , Gartner Research describes five types of analytics technologies: [11]